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This paper identifies variables, research design, and data collection techniques used in testing a linear hypothesis that high employee satisfaction is correlated with low employee absenteeism. It also identifies strategies that can be used to minimize problems encountered while testing the hypothesis.
A variable can be defined as the characteristic that can be placed in two or more categories. To test this hypothesis, variables such as gender, amount of the work that an employee performs, work frequency, job group level, and motivational activities can be used (Hall, 2000).
Extraneous variables are those which can influence the judgment about the relationship among the variables that a researcher is examining through the introduction of undesirable error to the results (Dereshiwsky, 2001). In this hypothesis, the extraneous variables may include the pre-knowledge of work requirements by employees, health condition of the employees, and employee promotions. These extraneous variables can be controlled by adjusting the result using random assignment of research questionnaires and limiting the time frame of the research to one season. However, some extraneous variables such as sick leaves of employees can be beyond the control of the researcher.
In this study, the use of surveys will be highly efficient to find the reasons that employees see as the most important in their coming to work. Observation method will also help to identify motivational level of employees. Use of questionnaires is recommended because it will enable respondents to give answers without the feeling of being pressured. It can also help in capturing any relevant information that was not factored in initially (Ratner, 2010).
Observation and questionnaires remain the most appropriate data collection techniques. Questionnaires ensure anonymity of respondents and can be used with a large number of groups. They also ensure the uniformity of questions that the researcher is asking. Observation method, on the other hand, will help the researcher to collect data without any biases.
Correlation coefficient denotes the strength of linear relationship among the variables. In case r = - 70, it means that there is a strong negative relationship between employee satisfaction and their absenteeism. That is, employees tend to become increasingly absent when satisfaction is low. On the other hand, the possible problems that can arise in this study are resistance by employees to give truthful answers and differences in social environment between female and male employees. The solution is to observe the behavior of employees and factor in the error caused by social environmental differences between different genders.